Original Research Paper

European Actuarial Journal

, Volume 1, Issue 1, pp 131-157

First online:

Fast remote but not extreme quantiles with multiple factors: applications to Solvency II and Enterprise Risk Management

  • Matthieu ChauvignyAffiliated withMilliman, Paris
  • , Laurent DevineauAffiliated withMilliman, ParisLaboratoire SAF EA 2429, Institut de Science Financière et d’Assurances, Université de Lyon, Université Lyon 1
  • , Stéphane LoiselAffiliated withLaboratoire SAF EA 2429, Institut de Science Financière et d’Assurances, Université de Lyon, Université Lyon 1 Email author 
  • , Véronique Maume-DeschampsAffiliated withLaboratoire SAF EA 2429, Institut de Science Financière et d’Assurances, Université de Lyon, Université Lyon 1

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Abstract

For operational purposes, in Enterprise Risk Management or in insurance for example, it may be important to estimate remote (but not extreme) quantiles of some function f of some random vector. The call to f may be time- and resource-consuming so that one aims at reducing as much as possible the number of calls to f. In this paper, we propose some ways to address this problem of general interest. We then numerically analyze the performance of the method on insurance and Enterprise Risk Management real-world case studies.

Keywords

Quantile estimation Risk factors Enterprise Risk Management Accelerated algorithm Nested Simulations